{"id":510814,"date":"2024-10-25T09:13:25","date_gmt":"2024-10-25T16:13:25","guid":{"rendered":"https:\/\/jorgep.com\/blog\/?p=510814"},"modified":"2025-01-17T12:02:57","modified_gmt":"2025-01-17T19:02:57","slug":"what-makes-the-many-llms-different","status":"publish","type":"post","link":"https:\/\/jorgep.com\/blog\/what-makes-the-many-llms-different\/","title":{"rendered":"What Makes the many LLMs different?"},"content":{"rendered":"\n<div class=\"wp-block-columns has-theme-palette-7-background-color has-background is-layout-flex wp-container-core-columns-is-layout-2edb0647 wp-block-columns-is-layout-flex\" style=\"margin-top:0;margin-bottom:0\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:80%\">\n<p>Part of: <strong> <a href=\"https:\/\/jorgep.com\/blog\/series-ai-learnings\/\">AI Learning Series Here<\/a><\/strong><\/p>\n\n\n<style>.kadence-column395113_97b87a-23 > .kt-inside-inner-col,.kadence-column395113_97b87a-23 > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column395113_97b87a-23 > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column395113_97b87a-23 > .kt-inside-inner-col{flex-direction:column;}.kadence-column395113_97b87a-23 > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column395113_97b87a-23 > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column395113_97b87a-23{position:relative;}@media all and (max-width: 1024px){.kadence-column395113_97b87a-23 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column395113_97b87a-23 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column395113_97b87a-23\"><div class=\"kt-inside-inner-col\"><style>.wp-block-kadence-advancedheading.kt-adv-heading510545_15a085-99, .wp-block-kadence-advancedheading.kt-adv-heading510545_15a085-99[data-kb-block=\"kb-adv-heading510545_15a085-99\"]{font-size:var(--global-kb-font-size-sm, 0.9rem);font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading510545_15a085-99 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading510545_15a085-99[data-kb-block=\"kb-adv-heading510545_15a085-99\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading510545_15a085-99 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading510545_15a085-99[data-kb-block=\"kb-adv-heading510545_15a085-99\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<p class=\"kt-adv-heading510545_15a085-99 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading510545_15a085-99\">Quick Links:\u00a0<a href=\"https:\/\/jorgep.com\/blog\/resources-for-learning-ai\/\">Resources for Learning AI<\/a> | <a href=\"https:\/\/jorgep.com\/blog\/keeping-up-with-ai\/\">Keep up with AI<\/a> | <a href=\"https:\/\/jorgep.com\/blog\/list-of-ai-tools\/\" data-type=\"post\" data-id=\"402818\">List of AI Tools<\/a> | <a href=\"https:\/\/jorgep.com\/blog\/local-ai-series\/\" data-type=\"page\" data-id=\"519365\">Local AI<\/a><\/p>\n<\/div><\/div>\n\n\n<style>.kb-row-layout-id395113_d73e95-0d > .kt-row-column-wrap{align-content:start;}:where(.kb-row-layout-id395113_d73e95-0d > .kt-row-column-wrap) > .wp-block-kadence-column{justify-content:start;}.kb-row-layout-id395113_d73e95-0d > .kt-row-column-wrap{column-gap:var(--global-kb-gap-md, 2rem);row-gap:var(--global-kb-gap-none, 0rem );padding-top:var(--global-kb-spacing-xxs, 0.5rem);padding-bottom:var(--global-kb-spacing-xxs, 0.5rem);grid-template-columns:repeat(2, minmax(0, 1fr));}.kb-row-layout-id395113_d73e95-0d > .kt-row-layout-overlay{opacity:0.30;}@media all and (max-width: 1024px){.kb-row-layout-id395113_d73e95-0d > .kt-row-column-wrap{grid-template-columns:repeat(2, minmax(0, 1fr));}}@media all and (max-width: 767px){.kb-row-layout-id395113_d73e95-0d > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}}<\/style><div class=\"kb-row-layout-wrap kb-row-layout-id395113_d73e95-0d alignnone wp-block-kadence-rowlayout\"><div class=\"kt-row-column-wrap kt-has-2-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top\">\n<style>.kadence-column395113_df36f9-de > .kt-inside-inner-col,.kadence-column395113_df36f9-de > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column395113_df36f9-de > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column395113_df36f9-de > .kt-inside-inner-col{flex-direction:column;}.kadence-column395113_df36f9-de > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column395113_df36f9-de > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column395113_df36f9-de{position:relative;}@media all and (max-width: 1024px){.kadence-column395113_df36f9-de > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column395113_df36f9-de > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column395113_df36f9-de\"><div class=\"kt-inside-inner-col\"><style>.wp-block-kadence-advancedheading.kt-adv-heading395113_b3212c-b9, .wp-block-kadence-advancedheading.kt-adv-heading395113_b3212c-b9[data-kb-block=\"kb-adv-heading395113_b3212c-b9\"]{text-align:center;font-size:var(--global-kb-font-size-sm, 0.9rem);line-height:60px;font-style:normal;background-color:#f5a511;}.wp-block-kadence-advancedheading.kt-adv-heading395113_b3212c-b9 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading395113_b3212c-b9[data-kb-block=\"kb-adv-heading395113_b3212c-b9\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading395113_b3212c-b9 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading395113_b3212c-b9[data-kb-block=\"kb-adv-heading395113_b3212c-b9\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<p class=\"kt-adv-heading395113_b3212c-b9 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading395113_b3212c-b9\">Subscribe to <a href=\"https:\/\/go.35s.be\/jtb\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>JorgeTechBits  newsletter<\/strong><\/a><\/p>\n<\/div><\/div>\n\n\n<style>.kadence-column395113_4b4b81-29 > .kt-inside-inner-col,.kadence-column395113_4b4b81-29 > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column395113_4b4b81-29 > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column395113_4b4b81-29 > .kt-inside-inner-col{flex-direction:column;}.kadence-column395113_4b4b81-29 > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column395113_4b4b81-29 > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column395113_4b4b81-29{position:relative;}@media all and (max-width: 1024px){.kadence-column395113_4b4b81-29 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column395113_4b4b81-29 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column395113_4b4b81-29\"><div class=\"kt-inside-inner-col\"><\/div><\/div>\n\n<\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\"><div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><a href=\"htthttps:\/\/jorgep.com\/blog\/book-dont-just-chat-delegate\/\"><img loading=\"lazy\" decoding=\"async\" width=\"640\" height=\"1024\" src=\"https:\/\/jorgep.com\/blog\/wp-content\/uploads\/CoverBook-01-640x1024.jpg\" alt=\"\" class=\"wp-image-520234\" style=\"aspect-ratio:0.6250142320391666;width:98px;height:auto\" srcset=\"https:\/\/jorgep.com\/blog\/wp-content\/uploads\/CoverBook-01-640x1024.jpg 640w, https:\/\/jorgep.com\/blog\/wp-content\/uploads\/CoverBook-01-188x300.jpg 188w, https:\/\/jorgep.com\/blog\/wp-content\/uploads\/CoverBook-01-768x1229.jpg 768w, https:\/\/jorgep.com\/blog\/wp-content\/uploads\/CoverBook-01-960x1536.jpg 960w, https:\/\/jorgep.com\/blog\/wp-content\/uploads\/CoverBook-01-1280x2048.jpg 1280w, https:\/\/jorgep.com\/blog\/wp-content\/uploads\/CoverBook-01.jpg 1600w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><figcaption class=\"wp-element-caption\"><a href=\"https:\/\/jorgep.com\/blog\/book-series-ai-dont-just-chat\/\" data-type=\"page\" data-id=\"520242\">Check out the Book Series<\/a><\/figcaption><\/figure>\n<\/div><\/div>\n<\/div>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading407818_afcbba-c7, .wp-block-kadence-advancedheading.kt-adv-heading407818_afcbba-c7[data-kb-block=\"kb-adv-heading407818_afcbba-c7\"]{font-size:var(--global-kb-font-size-sm, 0.9rem);font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading407818_afcbba-c7 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading407818_afcbba-c7[data-kb-block=\"kb-adv-heading407818_afcbba-c7\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading407818_afcbba-c7 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading407818_afcbba-c7[data-kb-block=\"kb-adv-heading407818_afcbba-c7\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<p class=\"kt-adv-heading407818_afcbba-c7 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading407818_afcbba-c7\">Have questions, ideas to share, or just want to connect? I\u2019d love to hear from you! Check out my <a href=\"https:\/\/jorgep.com\/blog\/about\/\">About Page<\/a> to learn more about me or connect with me.<\/p>\n\n\n\n<p>I did a general &#8220;understanding AI&#8221; session yesterday and one of the participants asked me an interesting question, which I do not think I have been asked before&#8230;  <\/p>\n\n\n\n<p><em><strong>What is the different between LLMs and what makes them unique and different from each other.<\/strong><\/em><\/p>\n\n\n\n<p>I thought it was a very valid question as Huggin face alone has over 1 million models in its library (although a lot of them are old already)  <\/p>\n\n\n\n<p>Hugging Face hosts a vast number of models because it aims to democratize access to state-of-the-art machine learning models for a wide range of tasks. The platform provides a centralized hub where developers and researchers can share, discover, and use models for various applications, including natural language processing (NLP), computer vision, and more.<\/p>\n\n\n\n<p>The models are different because they are designed to address specific tasks and use different architectures and training methods. For example, to take the models in Hugging Face, they have different categories (see HuggingFace: <a href=\"https:\/\/huggingface.co\/docs\/transformers\/v4.18.0\/en\/model_summary\" target=\"_blank\" rel=\"noopener noreferrer nofollow\">Summary of the models<\/a>)<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Autoregressive Models<\/strong>: These models, like GPT, are trained to predict the next token in a sequence, making them suitable for text generation tasks<a href=\"https:\/\/huggingface.co\/docs\/transformers\/v4.18.0\/en\/model_summary\" target=\"_blank\" rel=\"noopener noreferrer nofollow\">1<\/a>.<\/li>\n\n\n\n<li><strong>Autoencoding Models<\/strong>: Models like BERT fall into this category. They are trained to reconstruct the original input from a corrupted version, making them ideal for tasks like sentence classification and token classification<a href=\"https:\/\/huggingface.co\/docs\/transformers\/v4.18.0\/en\/model_summary\" target=\"_blank\" rel=\"noopener noreferrer nofollow\">1<\/a>.<\/li>\n\n\n\n<li><strong>Sequence-to-Sequence Models<\/strong>: These models use both an encoder and a decoder, making them suitable for tasks like translation, summarization, and question answering. T5 is an example of such a model<a href=\"https:\/\/huggingface.co\/docs\/transformers\/v4.18.0\/en\/model_summary\" target=\"_blank\" rel=\"noopener noreferrer nofollow\">1<\/a>.<\/li>\n\n\n\n<li><strong>Multimodal Models<\/strong>: These models can handle multiple types of input, such as text and images, and are designed for specific tasks that require this capability<a href=\"https:\/\/huggingface.co\/docs\/transformers\/v4.18.0\/en\/model_summary\" target=\"_blank\" rel=\"noopener noreferrer nofollow\">1<\/a>.<\/li>\n\n\n\n<li><strong>Retrieval-Based Models<\/strong>: These models are designed to retrieve relevant information from a large corpus of data, making them useful for tasks like information retrieval and question answering. <\/li>\n<\/ol>\n\n\n\n<p>Each model is optimized for different tasks and use cases, which is why there are so many models available on Hugging Face. This diversity allows users to find the best model for their specific needs and applications.<\/p>\n\n\n\n<p>The following table is my first attempt at providing model guidance to the task at hand: <\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Category<\/strong><\/td><td><strong>Basic Description<\/strong><\/td><td><strong>Model<\/strong><\/td><\/tr><tr><td><strong>Autoregressive Models<\/strong><\/td><td>A powerful model for text generation, capable of producing human-like text.<\/td><td>GPT-4, GPT-3, Mistral, Llama3<\/td><\/tr><tr><td><strong>Autoencoding Models<\/strong><\/td><td>Designed for tasks like sentence classification and token classification.&nbsp; RoBERTa is a version of BERT for better performance on NLP tasks.<\/td><td>BERT, RoBERTa<\/td><\/tr><tr><td><strong>Sequence-to-Sequence<\/strong><\/td><td>Suitable for translation, summarization tasks, and question answering.<\/td><td>T5, BART<\/td><\/tr><tr><td><strong>Multimodal Models<\/strong><\/td><td>Handles text, images, videos, and audio, suitable for various complex tasks.<\/td><td>Gemini, GPT-4,CLIP,<\/td><\/tr><tr><td><strong>Image Creation<\/strong><\/td><td>Generates images from textual descriptions, combining text and image modalities.<\/td><td>DALL-E, Stable Difusion,MidJourney<\/td><\/tr><tr><td><strong>Retrieval-Based Models<\/strong><\/td><td>Optimized for retrieving relevant information from large datasets.<\/td><td>DPR, BM25<\/td><\/tr><tr><td><strong>Financial Forecasting<\/strong><\/td><td>models are designed to handle various financial forecasting tasks and provide valuable insights for financial institutions.<\/td><td>FinGPT,BloombergGPT,LLM finance,<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p>Again &#8211; this is an initial post which I will be exploring more in the future.&#8211; GREAT question THANK YOU<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">See Also: <\/h2>\n\n\n\n<p><\/p>\n\n\n\n<p><a href=\"https:\/\/jorgep.com\/blog\/what-are-large-language-models-llm\/\">What Are Large Language Models (LLM) <\/a><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>I did a general &#8220;understanding AI&#8221; session yesterday and one of the participants asked me an interesting question, which I do not think I have been asked before&#8230; What is the different between LLMs and what makes them unique and different from each other. I thought it was a very valid question as Huggin face&#8230;<\/p>\n","protected":false},"author":2,"featured_media":427864,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_kad_blocks_custom_css":"","_kad_blocks_head_custom_js":"","_kad_blocks_body_custom_js":"","_kad_blocks_footer_custom_js":"","ngg_post_thumbnail":0,"episode_type":"","audio_file":"","podmotor_file_id":"","podmotor_episode_id":"","cover_image":"","cover_image_id":"","duration":"","filesize":"","filesize_raw":"","date_recorded":"","explicit":"","block":"","itunes_episode_number":"","itunes_title":"","itunes_season_number":"","itunes_episode_type":"","_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","footnotes":""},"categories":[441],"tags":[471,930,842,871,876],"class_list":["post-510814","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tech-talk","tag-ai","tag-ai-series","tag-chatgpt","tag-genai","tag-llm"],"taxonomy_info":{"category":[{"value":441,"label":"Tech Talk"}],"post_tag":[{"value":471,"label":"AI"},{"value":930,"label":"AI Series"},{"value":842,"label":"ChatGPT"},{"value":871,"label":"GenAi"},{"value":876,"label":"LLM"}]},"featured_image_src_large":["https:\/\/jorgep.com\/blog\/wp-content\/uploads\/FeaturedImage-Topic-AI-1024x512.png",1024,512,true],"author_info":{"display_name":"Jorge Pereira","author_link":"https:\/\/jorgep.com\/blog\/author\/jorge\/"},"comment_info":0,"category_info":[{"term_id":441,"name":"Tech Talk","slug":"tech-talk","term_group":0,"term_taxonomy_id":451,"taxonomy":"category","description":"","parent":0,"count":709,"filter":"raw","cat_ID":441,"category_count":709,"category_description":"","cat_name":"Tech Talk","category_nicename":"tech-talk","category_parent":0}],"tag_info":[{"term_id":471,"name":"AI","slug":"ai","term_group":0,"term_taxonomy_id":481,"taxonomy":"post_tag","description":"","parent":0,"count":167,"filter":"raw"},{"term_id":930,"name":"AI Series","slug":"ai-series","term_group":0,"term_taxonomy_id":940,"taxonomy":"post_tag","description":"","parent":0,"count":174,"filter":"raw"},{"term_id":842,"name":"ChatGPT","slug":"chatgpt","term_group":0,"term_taxonomy_id":852,"taxonomy":"post_tag","description":"","parent":0,"count":19,"filter":"raw"},{"term_id":871,"name":"GenAi","slug":"genai","term_group":0,"term_taxonomy_id":881,"taxonomy":"post_tag","description":"","parent":0,"count":93,"filter":"raw"},{"term_id":876,"name":"LLM","slug":"llm","term_group":0,"term_taxonomy_id":886,"taxonomy":"post_tag","description":"","parent":0,"count":19,"filter":"raw"}],"_links":{"self":[{"href":"https:\/\/jorgep.com\/blog\/wp-json\/wp\/v2\/posts\/510814","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/jorgep.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/jorgep.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/jorgep.com\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/jorgep.com\/blog\/wp-json\/wp\/v2\/comments?post=510814"}],"version-history":[{"count":0,"href":"https:\/\/jorgep.com\/blog\/wp-json\/wp\/v2\/posts\/510814\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/jorgep.com\/blog\/wp-json\/wp\/v2\/media\/427864"}],"wp:attachment":[{"href":"https:\/\/jorgep.com\/blog\/wp-json\/wp\/v2\/media?parent=510814"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/jorgep.com\/blog\/wp-json\/wp\/v2\/categories?post=510814"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/jorgep.com\/blog\/wp-json\/wp\/v2\/tags?post=510814"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}